Figure 1.
An additive genetic score helps predict HIV-1 disease progression.
Data are from Fellay et al. [7]: 1,071 individuals of Caucasian ancestry with HIV-1 are included in the analysis. The columns show the proportions of individuals that reached a progression outcome (CD4+ T cells <350/ul or initiation of combined antiretroviral treatment with CD4+ T cells <500/ul) during the first 5 years after estimated date of seroconversion in categories defined by HIV-1 viral load and by a simple additive genetic score, in which one unit is counted for each “protective” allele. The minimum score is 0 for individuals that are homozygous for the major allele at rs2395029 (a proxy for HLA-B*5701), rs9264942 (HLA-C -35 variant), rs9261174 (ZNRD1), and CCR5-Δ32. The maximal observed score is 3 since no individual was heterozygous or homozygous for the minor allele at all four sites. Individuals were grouped in three categories to clearly show that the genetic score refines the prediction of progression, beyond the information provided by viral load only, throughout the range of set point values.
Figure 2.
Project framework: human genome resequencing of hemophilia A individuals exposed to HIV-contaminated factor VIII in 1979–1984, yet uninfected.
Figure 3.
Genome-wide and large-scale studies published since 2007 in the HIV field.
The number of studies is in parentheses. Diverse sets of results and data are compiled in an encyclopedia of overlaps between studies (http://www.hostpathogen.org/). This approach serves to identify networks used by HIV-1 to support its replication. Figure updated from reference [55] (http://F1000.com/Reports/Biology/content/1/71).
Figure 4.
Predicted interaction networks of genes identified as HIV dependency factors in siRNA/shRNA screens [72]–[75].
Links have been predicted using STRING (http://string.embl.de/). Predicted interactions are depicted according to the type of available evidence. The interactions (see color labels) include direct (physical) and indirect (functional) associations; they are derived from four sources: genomic context, high-throughput experiments, conserved co-expression, and previous knowledge from literature. The nature of the supporting evidence is indicated by the color lines: yellow, text mining; purple, experimental; red, gene fusion; light blue, protein–protein interactions; blue, genomic co-occurrence evidence.